8 research outputs found

    Predicting Vapor-Phase Concentrations for the Assessment of the Odor Perception of Fragrance Chemicals Diluted in Mineral Oil

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    In this study, the Henry’s law methodology is applied to predict the release of odorants present in single and multicomponent fragrance mixtures diluted in mineral oil, a simplified matrix used in cosmetic products. To attain this goal, the experimental Henry’s law constant (<i>H</i>) of each odorant in each studied fragrance system (containing one, two, three, or four odorants) was first evaluated by plotting their liquid phase and experimental vapor phase concentrations assessed by headspace gas chromatography. From that point, the <i>H</i> value of each odorant in the multicomponent fragrance system was predicted from its corresponding <i>H</i><sup>exp</sup> in the single fragrance component system. The theoretical vapor-phase concentrations were also calculated using the activity coefficients for vapor–liquid equilibria by applying the thermodynamic UNIFAC model. The odor intensity and character of the studied fragrance systems were assessed through the Stevens’s power law and Strongest Component models (psychophysical models). This study confirmed that the headspace concentrations and odor intensity of each odorant present in a multicomponent fragrance mixture dissolved in mineral oil can be efficiently predicted from its corresponding <i>H</i> determined when present alone in the simplified matrix, for low concentrations. Also, comparing both methodologies, UNIFAC and Henry’s law, it was concluded that Henry’s law is a better predictive model for the vapor–liquid equilibria, showing lower deviations from the experimental data. Therefore, the proposed predictive mathematical model can be attractive for the assessment of sensory quality of multicomponent fragrance systems in early formulation stages

    Main epidemiological characteristics of the two Intervention phases.

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    *<p>All wards were monitored the same day for a 30 minute session except for Intensive Care Unit and Emergency Department where two different observations by two different hand hygiene monitor team (HHMT) members were planned.</p

    Poisson Exponential Weighted Moving Average control chart (statistical healthcare-acquired MRSA colonization/infection process control).

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    <p>Data are shown in cases per 10,000 patient-days (2007–2011 period). A set of points is highlighted (circles) and the rules (special causes) are shown. See legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047200#pone-0047200-g001" target="_blank">figure 1</a> for control charts rules explanation.</p

    Binomial control chart (statistical hand hygiene compliance process control during phase 2 according HCW categories).

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    <p>A: nursing assistants. B: nurses. C: physicians. Sets of points are highlighted (circles) and the rules (special causes) are shown. Three zones (C, B, A) that emanate outward from the center line (CL) are labeled (often referred as “sigma limits”). See legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047200#pone-0047200-g001" target="_blank">Figure 1</a> for control charts rules explanation.</p

    Binomial control chart (statistical hand hygiene compliance process control during phase 2 according working areas).

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    <p>A: medical-surgical wards. B: intensive care unit. C: emergency department. Sets of points are highlighted (circles) and the rules (special causes) are shown. Three zones (C, B, A) that emanate outward from the center line (CL) are labeled (often referred as “sigma limits”). See legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047200#pone-0047200-g001" target="_blank">Figure 1</a> for control charts rules explanation.</p

    Poisson control chart (statistical overall alcohol hand rub consumption [liters/1,000 patient-days] process control).

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    <p>Data are shown in a bimonthly fashion from 4b m08 (July–August 2008) to 6bm11 (November–December 2011). Set of points are highlighted (circles) and the rules (special causes) are shown. See legend in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047200#pone-0047200-g001" target="_blank">figure 1</a> for control charts rules explanation.</p
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